logo
ResearchBunny Logo
News media in crisis: a sentiment and emotion analysis of US news articles on unemployment in the COVID-19 pandemic

Social Work

News media in crisis: a sentiment and emotion analysis of US news articles on unemployment in the COVID-19 pandemic

L. Yu and L. Yang

This study, conducted by Lingli Yu and Ling Yang, explores how the *New York Times* portrayed pandemic-induced unemployment in 2020, revealing a more positive sentiment overall. Dominant emotions of trust and anticipation are evaluated while linking them to the pandemic's progression, policy responses, and racial inequality protests.

00:00
00:00
~3 min • Beginner • English
Abstract
News media play an indispensable role in disseminating information and shaping public perception during times of crisis. This study, integrating sentiment, emotion, discourse, and timeline analyses together, conducts a corpus-based sentiment analysis of the news articles on unemployment from the New York Times in 2020 to capture the emotional dynamics conveyed by the newspaper as the pandemic-induced unemployment developed in the US. The results reveal that positive sentiment in the news articles on unemployment is significantly higher than negative sentiment. In emotion analysis, "trust" and "anticipation" rank the first and second among the eight emotions, while "fear" and "sadness" top the negative emotions. Complemented with a discourse analysis approach, the study reveals that the change of the sentiments and emotions over time is linked with the evolution of the pandemic and unemployment, the policy response as well as the protests against ethnic inequalities. This study highlights the important role mainstream news media play in information dissemination and solution-focused reportage at the time of severe crisis.
Publisher
Humanities & Social Sciences Communications
Published On
Jun 28, 2024
Authors
Lingli Yu, Ling Yang
Tags
sentiment analysis
unemployment
pandemic
New York Times
emotions
discourse analysis
racial inequality
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny